Software engineering metrics and models
Software engineering metrics and models
Robust regression for developing software estimation models
Journal of Systems and Software
Estimating Software Project Effort Using Analogies
IEEE Transactions on Software Engineering
A replicated assessment and comparison of common software cost modeling techniques
Proceedings of the 22nd international conference on Software engineering
Software Engineering Economics
Software Engineering Economics
An Empirical Study of Analogy-based Software Effort Estimation
Empirical Software Engineering
Using Prior-Phase Effort Records for Re-estimation During Software Projects
METRICS '03 Proceedings of the 9th International Symposium on Software Metrics
What Should You Optimize When Building an Estimation Model?
METRICS '05 Proceedings of the 11th IEEE International Software Metrics Symposium
A Comparison of Software Project Overruns-Flexible versus Sequential Development Models
IEEE Transactions on Software Engineering
Cross-company and single-company effort models using the ISBSG database: a further replicated study
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Power-Laws in a Large Object-Oriented Software System
IEEE Transactions on Software Engineering
Phase distribution of software development effort
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
Why comparative effort prediction studies may be invalid
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
Investigating the use of Support Vector Regression for web effort estimation
Empirical Software Engineering
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Many research projects on software estimation use software size as a major explanatory variable. However, practitioners sometimes use the ratio of effort for early phase activities such as planning and requirement analysis, to the effort for the whole development phase of the software in order to estimate effort. In this paper, we focus on effort estimation based on the effort for early phase activities. The goal of the research is to examine the relationship of early phase effort and software size with software development effort. To achieve the goal, we built effort estimation models using early phase effort as an explanatory variable, and compared the estimation accuracies of these models to the effort estimation models based on software size. In addition, we built estimation models using both early phase effort and software size. In our experiment, we used ISBSG dataset, which was collected from software development companies, and regarded planning phase effort and requirement analysis effort as early phase effort. The result of the experiment showed that when both software size and sum of planning and requirement analysis phase effort were used as explanatory variables, the estimation accuracy was most improved (Average Balanced Relative Error was improved to 75.4% from 148.4%). Based on the result, we recommend that both early phase effort and software size be used as explanatory variables, because that combination showed the high accuracy, and did not have multicollinearity issues.